It’s 3 a.m. A deployment from earlier that evening introduced a subtle bug and a critical service goes down. Your pager goes off. But by the time you open your laptop, an AI agent has already triaged the incident, traced the root cause back to a specific code change, and opened a pull request with a fix. Your job: read the analysis, review the code, and hit merge.

In this session, I show how AI agents can take over the operational side of DevOps. Unlike development agents, which work step by step with human approval, ops agents need to act autonomously: detecting anomalies, investigating root causes, and preparing fixes while no one is watching. You’ll see how to design an agent pipeline that monitors your production environment, performs automated triage when something breaks, and presents both a root cause analysis and a code fix for human review.

You’ll go home with a concrete architecture for agent-driven incident response and a realistic view of what is production-ready today and what is still future music.